Development and validation of a black carbon mixing state resolved three‐dimensional model: Aging processes and radiative impact

[1] A new two-dimensional aerosol bin scheme, which resolves both aerosol size and black carbon (BC) mixing state for BC aging processes (e.g., condensation and coagulation) with 12 size × 10 mixing state bins, has been developed and implemented into the WRF-chem model (MS-resolved WRF-chem). The mixing state of BC simulated by this model is compared with direct measurements over the East Asian region in spring 2009. Model simulations generally reproduce the observed features of the BC mixing state, such as the size-dependent number fractions of BC-containing and BC-free particles and the coating thickness of BC-containing particles. This result shows that the model can simulate realistic BC mixing states in the atmosphere if condensation and coagulation processes are calculated explicitly with the detailed treatment of BC mixing state. Sensitivity simulations show that the condensation process is dominant for the growth of thinly coated BC particles, while the coagulation process is necessary to produce thickly coated BC particles. Off-line optical and radiative calculations assuming an average mixing state for each size bin show that the domain- and period-averaged absorption coefficient and heating rate by aerosols are overestimated by 30–40% in the boundary layer, compared with a benchmark simulation with the detailed treatment of mixing state. The absolute value of aerosol radiative forcing is also overestimated (10%, 3 W m–2) at the surface. However, these overestimations are reduced considerably when all the parameters (including mass and number concentration) are calculated with the simple treatment of mixing state. This is because the overestimation of radiative parameters due to higher absorption efficiency (compared with the benchmark simulation) is largely canceled by the underestimation of BC concentrations due to efficient wet removal processes. The overall errors in radiative forcing can be much smaller because of this cancellation, but for the wrong reasons.

[1]  N. Takegawa,et al.  Wet removal of black carbon in Asian outflow: Aerosol Radiative Forcing in East Asia (A‐FORCE) aircraft campaign , 2012 .

[2]  Steven J. Ghan,et al.  Coupling aerosol-cloud-radiative processes in the WRF-Chem model: Investigating the radiative impact of elevated point sources , 2008 .

[3]  Michael Q. Wang,et al.  An inventory of gaseous and primary aerosol emissions in Asia in the year 2000 , 2003 .

[4]  James G. Hudson,et al.  Evaluation of aerosol direct radiative forcing in MIRAGE , 2001 .

[5]  J. Hansen,et al.  Radiative forcing and climate response , 1997 .

[6]  Kaoru Sato,et al.  Design of the NIPR trajectory model , 2005 .

[7]  D. Blake,et al.  Radiative impact of mixing state of black carbon aerosol in Asian outflow , 2008 .

[8]  Spyros N. Pandis,et al.  Optimizing model performance: variable size resolution in cloud chemistry modeling , 2001 .

[9]  T. Bond,et al.  Limitations in the enhancement of visible light absorption due to mixing state , 2006 .

[10]  J. Barnard,et al.  Technical Note: Evaluation of the WRF-Chem "aerosol chemical to aerosol optical properties" module using data from the MILAGRO campaign , 2010 .

[11]  Yutaka Kondo,et al.  Effects of Mixing State on Black Carbon Measurements by Laser-Induced Incandescence , 2007 .

[12]  D. Blake,et al.  Evolution of mixing state of black carbon particles: Aircraft measurements over the western Pacific in March 2004 , 2007 .

[13]  N. Takegawa,et al.  Formation and transport of aerosols in Tokyo in relation to their physical and chemical properties: a review , 2010 .

[14]  F. Binkowski,et al.  The Regional Particulate Matter Model 1. Model description and preliminary results , 1995 .

[15]  B. Vogel,et al.  Modeling aerosols on the mesoscale‐γ: Treatment of soot aerosol and its radiative effects , 2003 .

[16]  R. Turco,et al.  Modeling coagulation among particles of different composition and size , 1994 .

[17]  M. Jacobson Control of fossil‐fuel particulate black carbon and organic matter, possibly the most effective method of slowing global warming , 2002 .

[18]  M. Jacobson A physically‐based treatment of elemental carbon optics: Implications for global direct forcing of aerosols , 2000 .

[19]  M. Jacobson,et al.  Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols , 2022 .

[20]  J. Seinfeld,et al.  Impact of nonabsorbing anthropogenic aerosols on clear‐sky atmospheric absorption , 2006 .

[21]  M. Jacobson Development and application of a new air pollution modeling system—II. Aerosol module structure and design , 1997 .

[22]  S. Ghan,et al.  A parameterization of aerosol activation: 2. Multiple aerosol types , 2000 .

[23]  Georg A. Grell,et al.  Fully coupled “online” chemistry within the WRF model , 2005 .

[24]  A. Kirkevåg,et al.  Aerosol-climate interactions in the CAM-Oslo atmospheric GCM and investigation of associated basic shortcomings , 2008 .

[25]  Xindi Bian,et al.  MIRAGE: Model description and evaluation of aerosols and trace gases , 2004 .

[26]  Yutaka Kondo,et al.  Seasonal and diurnal variations of submicron organic aerosol in Tokyo observed using the Aerodyne aerosol mass spectrometer , 2006 .

[27]  Yugo Kanaya,et al.  Comparison of Black Carbon Mass Concentrations Observed by Multi-Angle Absorption Photometer (MAAP) and Continuous Soot-Monitoring System (COSMOS) on Fukue Island and in Tokyo, Japan , 2013 .

[28]  Matthew West,et al.  Particle‐resolved simulation of aerosol size, composition, mixing state, and the associated optical and cloud condensation nuclei activation properties in an evolving urban plume , 2010 .

[29]  C. O'Dowd,et al.  Primary versus secondary contributions to particle number concentrations in the European boundary layer , 2011 .

[30]  Tong Zhu,et al.  Spatial and temporal variations of aerosols around Beijing in summer 2006: Model evaluation and source apportionment , 2009, Journal of Geophysical Research.

[31]  D. Blake,et al.  Emissions of Black Carbon, Organic, and Inorganic Aerosols From Biomass Burning in North America and Asia in 2008 , 2011 .

[32]  V. Ramanathan,et al.  Aerosols, Climate, and the Hydrological Cycle , 2001, Science.

[33]  Anthony S. Wexler,et al.  Modelling urban and regional aerosols—I. model development , 1994 .

[34]  Axel Lauer,et al.  MADE-in : a new aerosol microphysics submodel for global simulation of insoluble particles and their mixing state , 2011 .

[35]  Steven J. Ghan,et al.  Impact on modeled cloud characteristics due to simplified treatment of uniform cloud condensation nuclei during NEAQS 2004 , 2007 .

[36]  O. Boucher,et al.  The aerosol-climate model ECHAM5-HAM , 2004 .

[37]  Chien Wang,et al.  A Modeling Study on the Climate Impacts of Black Carbon Aerosols , 2002 .

[38]  Leonard K. Peters,et al.  A new lumped structure photochemical mechanism for large‐scale applications , 1999 .

[39]  S. Gong,et al.  Effects of black carbon aging on air quality predictions and direct radiative forcing estimation , 2011 .

[40]  N. Takegawa,et al.  Consistency and Traceability of Black Carbon Measurements Made by Laser-Induced Incandescence, Thermal-Optical Transmittance, and Filter-Based Photo-Absorption Techniques , 2011 .

[41]  M. Simmel,et al.  Condensation and activation in sectional cloud microphysical models , 2006 .

[42]  Y. Yokouchi,et al.  Secondary organic aerosol formation in urban air: Temporal variations and possible contributions from unidentified hydrocarbons , 2009 .

[43]  R. C. Easter,et al.  Simulating the evolution of soot mixing state with a particle-resolved aerosol model , 2008, 0809.0875.

[44]  A. Kitoh,et al.  Correction to “Future changes and uncertainties in Asian precipitation simulated by multiphysics and multi‐sea surface temperature ensemble experiments with high‐resolution Meteorological Research Institute atmospheric general circulation models (MRI‐AGCMs)” , 2013 .

[45]  R. C. Easter,et al.  Estimating Black Carbon Aging Time-Scales with a Particle-Resolved Aerosol Model , 2009, 0903.0029.

[46]  M. Jacobson Analysis of aerosol interactions with numerical techniques for solving coagulation, nucleation, condensation, dissolution, and reversible chemistry among multiple size distributions , 2002 .

[47]  N. Takegawa,et al.  Aging of black carbon in outflow from anthropogenic sources using a mixing state resolved model: Model development and evaluation , 2009 .

[48]  N. Takegawa,et al.  Impact of new particle formation on the concentrations of aerosols and cloud condensation nuclei around Beijing , 2011 .

[49]  Y. Kondo,et al.  Performance of a newly designed continuous soot monitoring system (COSMOS). , 2008, Journal of environmental monitoring : JEM.

[50]  G. Grell,et al.  Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology‐chemistry‐aerosol model , 2006 .

[51]  R. Ruedy,et al.  MATRIX (Multiconfiguration Aerosol TRacker of mIXing state): an aerosol microphysical module for global atmospheric models , 2008 .

[52]  F. Bowman,et al.  A detailed aerosol mixing state model for investigating interactions between mixing state, semivolatile partitioning, and coagulation , 2010 .

[53]  Yutaka Kondo,et al.  Aging of black carbon in outflow from anthropogenic sources using a mixing state resolved model: 2. Aerosol optical properties and cloud condensation nuclei activities , 2009 .

[54]  C. N. Hewitt,et al.  A global model of natural volatile organic compound emissions , 1995 .

[55]  M. Chou,et al.  A Solar Radiation Model for Use in Climate Studies , 1992 .

[56]  H. D. Orville,et al.  Bulk Parameterization of the Snow Field in a Cloud Model , 1983 .

[57]  Y. Kondo,et al.  Dependence of Laser-Induced Incandescence on Physical Properties of Black Carbon Aerosols: Measurements and Theoretical Interpretation , 2010 .

[58]  V. Ramanathan,et al.  Global and regional climate changes due to black carbon , 2008 .

[59]  V. Ramanathan,et al.  Reduction of tropical cloudiness by soot , 2000, Science.

[60]  Chien Wang,et al.  Distribution and direct radiative forcing of carbonaceous and sulfate aerosols in an interactive size-resolving aerosol-climate model , 2008 .

[61]  Jerome D. Fast,et al.  Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) , 2008 .

[62]  J. Hansen,et al.  Climate Effects of Black Carbon Aerosols in China and India , 2002, Science.

[63]  Tong Zhu,et al.  Spatial and temporal variations of aerosols around Beijing in summer 2006: 2. Local and column aerosol optical properties , 2010 .

[64]  Tami C. Bond,et al.  Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom , 2006 .